Autonomous Car using end to end Deep Learning |
Author(s): |
| Babysyla. L , COLLEGE OF ENGINEERING,TRIVANDRUM; Shijo George, COLLEGE OF ENGINEERING,TRIVANDRUM |
Keywords: |
| Autonomous Car |
Abstract |
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A Autonomous car (also known as self-driving car, or driverless car) has the capability to sense about its environment and navigating without human decision. Self-driving cars are the next generation technology which promise road safety. Implementing a self-driving car is difficult which includes many parts. Some of them are traffic light identification and classification, MPC controller, Path planning, behavioral cloning, vehicle detection and distance calculation, PID controller, object detection and identification, lane finding. The first and most important part is the behavioral cloning part which can be implemented by using CNN (Convolutional Neural Network) nvidia end to end deep learning model, widely used model for behavioral cloning. In this paper we have explained how to implement an autonomous car using the end to end deep learning model on simulators and real world games. |
Other Details |
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Paper ID: IJSRDV6I70224 Published in: Volume : 6, Issue : 7 Publication Date: 01/10/2018 Page(s): 386-389 |
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